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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah Kursor Jurnal Mahasiswa Jurusan Arsitektur Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Management Research and Studies
Fitra Abdurrachman Bachtiar
Fakultas Ilmu Komputer - Universitas Brawijaya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Social Sciences

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Segmentasi Pelanggan Menggunakan Metode Fuzzy C-Means Clustering Berdasarkan LRFM Model Pada Toko Sepatu (Studi Kasus: Ride Inc Kota Malang) Muhammad Taufik Dharmawan; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Ride Inc. is a leather shoe store established in 2012 in the city of Malang. Customer data owned has not been utilized to obtain values that are able to help Ride Inc. in creating business strategies to gain and retain customers. Customer segmentation is groups of customers who have a similarity of characteristics that able to provide information. The characteristics of customers can be seen by applying LRFM (Length, Recency, Frequency, and Monetary) model. Methods used in grouping customers are Fuzzy C-Means clustering. Elbow method used to help the process of determining the best number of clusters iteratively. The data used from the Ride Inc. are 522 customers data in the period of July 2017 until March 2018. The results shows that there are two and three clusters that formed based on elbow method that are then implemented into the Fuzzy C-Means. Customer segment analysis based on the LRFM model formed in the rank of profitable customer group based on the highest value of L, F, and also M and the lowest R. Dashboard visualization become the output of the research based on the value of the given LRFM to Ride Inc. The average score of usability testing from 2 respondents is 65. This means that Ride Inc. receive the dashboard visualization.
Analisis Segmentasi Pelanggan Dengan RFM Model Pada Pt. Arthamas Citra Mandiri Menggunakan Metode Fuzzy C-Means Clustering Wiratama Ahsani Taqwim; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. Arthamas Citra Mandiri is a money changer company. The company has not applied CRM (Customer Relationship Management) so that company still applying the same service to all customers. Some customers often have transactions, but on the other sides, some customers are rarely. The data used in this research is the transaction history from January 2017 until December 2017 and it including 981 transactions. Segmentation is a process to identify customers so it can help us to know the profitable customers for the company. The characteristics of the customers could be seen from RFM (Recency, Frequency, Monetary) which means Recency (the last customer transaction), Frequency (the number of transactions), and Monetary (the amount of money spend). One of the clustering methods that can be used in this research is Fuzzy C-Means. Elbow method is used to help the researcher determine the best cluster for Fuzzy C-Means. Partition Coefficient and Euclidean Distance are validation methods to knowing the best cluster. In this research, cluster 3 is the best results. Cluster results are visualized by the dashboard with some graphics which contains segmentation customer based on RFM value of PT. Arthamas Citra Mandiri customers transactions. Dashboard visualization is given to the company and researcher doing usability testing to know the effectiveness of the dashboard visualization. The results of the usability testings are 77.5. It means the dashboard is an acceptable categorized or can be accepted by the company.
Pengembangan Aplikasi E-Learning Dengan Menerapkan Metode Gamification Irwan Suprianto; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Online learning platform, also known as e-learning is a very popular media for education these days. the lack of interest from the students to the media used by the school are the main cause for the ineffective of the e-learning. interest and student satisfaction are influenced by some factor such as the feature and content does not help the student finishes their assignment so they decided not to use the application again. in order to combat these problems, a new e-learning app are developed implementing game method for the feature and content. This method are called Gamification. interest is the main target for gamification
Peringkasan Teks Untuk Deteksi Kejadian Pada Dokumen Twitter Berbahasa Indonesia Dengan Metode Affinity Propagation Rezky Dermawan; Fitra A. Bachtiar; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is on of many social medias where the user often tell about events that are happenings around them, ranging from insignificant to important things. Twitter's qualities where the user could make a tweet anywhere in a brief time frame, make it feasible for critical information to appear before the media even report it. However, it is difficult to comprehend what relevant events are occuring in a specific region because of the sheer size of scale and diverse sort of tweets. Accordingly, there is a need of a framework that could do pertinent event detection and give a summary about that event. In light of the reason expressed over, this research center around text summarization for event detection of Indonesian Twitter archive utilizing Affinity Propagation. Through the process of clustering, the resulting clusters become the representation of events occuring in a specific place and time period. Two kinds of data are used for assessment, first is themathic which has spesific kind of event happening in the time frame of the tweet and second is generic where the tweet are taken from an arbitary time frame. In order to get the best resulting cluster, parametesr of Affinity Propagation are evaluated reuslting in preference of quartile 3 dan minimum, damping factor of 0,3 and 0,5, changed limit of 1 and 2, iteration maximum of 250 as the best parameters for the thematic and generic data. The result of tweet summary from the clustering process are then compared with a specialist's summary to be evaluated by ROGUE-N method, scoring 0,459 and 0,4009 respectively on two kinds of data.
Pengembangan Aplikasi Native Pelaporan Kerusakan Jalan Pada Platform iOS Alfin Taufiqurrahman; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Road damage is a common thing found on city streets. Not a bit of road damage causes discomfort in driving to cause accidents. Not a few people are anxious about the road conditions. The amount of public desire to be able to report road damage so that roads can be repaired quickly is quite high. Therefore, a facility is needed for the community to be able to easily and quickly convey their concerns regarding road damage. The Laporjalan application offers these conveniences. By using the geotagging feature and taking pictures with an iOS-based smartphone camera. Using the Firebase database as online storage, users can also find out which roads have road damage, from the level of minor damage to severe damage and monitor the progress of damaged road reports that have been sent. The road damage report sent by the user will be used by the relevant agency as additional information for road repairs. Developed with an iterative method, Laporjalan applications can easily adjust its features to user needs. Based on the results of testing with usability testing, obtained a value of 74 for Laporjalan application, where this value falls into the category of acceptability rating with the level is good so that this application can be said according to user needs.
Perbandingan Double Moving Average dan Double Exponential Smoothing untuk Peramalan Jumlah Kedatangan Wisatawan Mancanegara di Bandara Ngurah Rai Cinthia Vairra Hudiyanti; Fitra Abdurrachman Bachtiar; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Every year the number of international tourist arrivals in Bali always increases (BPS, Statistics Indonesia). Increasing the number of international tourist arrivals will have an impact on the availability of facilities, infrastructure, and services for the airport or Angkasa Pura I. Many things affect foreign arrivals, resulting in the need forecasting the number of foreign arrivals whose results can be used by Angkasa Pura I as the airport manager and local government to improve services. This research forecasting is done using Double Moving Average and Double Exponential Smoothing. Accuracy calculation is done by using Mean Absoulte Percentage Error (MAPE). The data used are 120 data, from January 2008 to December 2017, and obtained from the official website of Statistics Indonesia. From this study testing in 2017 found the best time order value for the Double Moving Average is 2 and Double Exponential Smoothing with parameter 𝛼 = 0.4. From these parameter values, the MAPE Double Moving Average value is 10,522 and the MAPE Double Exponential Smoothing value is 3,355. At Double Exponential Smoothing has a value below 10, it is said to be very good, while the Double Moving Average with a value above 10 is said to be good. It can be concluded that Double Exponential Smoothing has better accuracy than Double Moving Average in forecasting the number of arrivals of foreign tourists at Ngurah Rai Airport.
Klasifikasi Penyakit Kelamin Pada Wanita Dengan Menggunakan Kombinasi Metode K-Nearest Neighbor Dan Naive Bayes Classifier Dimas Angga Nazaruddin; Fitra Abdurrachman Bachtiar; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Venereal or Sexually Transmitted Disease (STD) are still a public health problem in developed and developing countries. Expert stated that health problems caused by venereal disease are higher in women. symptoms experienced have similarities between one and other venereal disease. Lack of knowledge possessed by patients can cause more severe. Therefore, to reduce the level of problems in self-examination, research is needed to classifying female veneral disease to find out the types of infectious diseases. Various methods can be used in classification. including using K-Nearest Neighbor (KNN) and Naive Bayes Classifier. The combination of these two methods has advantages that include no need to discretize more on continuous variables. So that in this study the KNN and Naive Bayes Classifier method will be combined to classify venereal diseases, especially for women because both of these methods have a high degree of accuracy in studying a disease so it is expected to predict probabilities based on testing data. In this study the accuracy test of the combination of the K-Nearest Neighbor and Naive Bayes Classifier methods was 97.5% using an average accuracy and 99.17% using the confusion matrix for the nearest number of neighbors as K = 5.
Klasifikasi Status Gizi pada Balita Menggunakan Metode Extreme Learning Machine dan Algoritme Genetika Nabila Lubna Irbakanisa; Imam Cholissodin; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Nutritional problem is one of serious problems. Because nutrition does not only concern in survival, but also relates to the quality of someone's life. In this case, the examination of child nutrient by medical personnel is generally done by archiving, namely by recording manually, and then analyzed. But by doing the analysis manually, it makes the vulnerability of inaccuracy in identifying nutritional status, and takes longer time because it is less practical. Based on these problems, the authors apply the Extreme Learning Machine (ELM) method and Genetic Algorithm to classify nutritional status in toddlers quickly and accurately. In this research, Genetic Algorithms used for finding the best input weight, which will then be used to determine the value of nutritional status using ELM. After testing, obtained an average accuracy of ELM - Genetic Algorithm is 72.3529% with the number of popsize is 100, 34 iterations, crossover rate 0.6, mutation rate 0.4, and 2 hidden neuron. While the accuracy obtained from the ELM is 67.6471%. The result also shows that the addition if Genetic Algorithm on ELM can improve the accuracy.
Pengembangan Sistem Informasi Review Smartphone Studi Pada TNT Cell Bojonegoro Aulia Septi Pertiwi; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

88% smartphone users read reviews about smartphone. Smartphone reviews can be found on various websites. TNT Cell is one of the mobile counter that sells various brands of smartphone. One of business process at TNT Cell is the consultation process about smartphone, some of the customers can't understand well about the advantages and disadvantages of smartphone, although it has been explained by the officer. That case will affects the process of customer decision making. Based on these problems an information system about smartphone review was developed. This system will give the customer information about smartphones by review from several websites and conducting sentiment analysis on reviews. Web scraping methods are used in this system to extract reviews from sites priceprice.com, pricebook.co.id, and iprice.co.id. In the process of sentiment analysis, one of the classification methods that used was Support Vector Machine. The software development method that used in this research is the waterfall model method. The testing technique that used on this research are validation testing, compatibility testing, and usability testing. The result of validation testing is all of the given test case are valid, that mean the system has been built appropriate with the user requirement.
Pengembangan Sistem Pelaporan Kerusakan Jalan Berbasis Android Untuk Daerah Kota Malang Menggunakan Konsep Crowdsource Ardi Wicaksono; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In the city of Malang, there are many traffic jams at many points, both on the protocol road and on the roads of the village. Apart from the fact that Malang City has a large population, the density of transportation or congestion that occurs is also caused by damage to the road. This is also a factor in the occurrence of traffic accidents on the highway. Damages to the road cannot be quickly handled by the Malang City government. This is because the city of Malang has a fairly large area of 110.6 square kilometers, and the survey process that must be carried out is quite time-consuming and costly. Difficulties are also experienced by people who want to report a road damage, including because they do not know the procedures that must be done to report. The Road Reporting System, offers a reporting mechanism, whereby the reporter can send his report anywhere in the city of Malang to the Binamarga official in Malang City, and the Malang City office will be easier to collect road damage data. The Road Reporting System consists of two applications, namely, a reporting application built on the Android platform for reporters, and an admin application built on the nodeJs web application platform for Malang City services.
Co-Authors AA Sudharmawan, AA Abidatul Izzah Abu Wildan Mucholladin Achmad Arwan Achmad Basuki Achmad Fahlevi Achmad Firmansyah Sulaeman Achmad Hanim Nur Wahid Achmad Ridok Adam Hendra Brata Adam Syarif Hidayatullah Adam Syarif Hidayatullah Adinugroho, Sigit Aditya Rachmadi Aditya Rachmadi, Aditya Admaja Dwi Herlambang, Admaja Dwi Admi Rut Sinana Afida, Latansa Nurry Izza Afifurrijal Afifurrijal Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Fairuzabadi Ahmad Foresta Azhar Zen Aisyah Awalina Aisyah Awalina Aisyatul Maulidah Aisyatul Maulidah Akhmad Lazuardi Alaikal Fajri Nur Alfian Aldi Fianda Putra Alfi Nur Rusydi Alfin Taufiqurrahman Alfirsa Damasyifa Fauzulhaq Alhasyimi, Dana Mustofa Alifi Lazuardi Gunawan Amalia Kusuma Akaresti Andi Alifsyah Dyasham Anggit Chalilur Rahman Anita Rizky Agustina Anita Rizky Agustina Anjasari, Ni Luh Made Beathris Anjumi Kholifatu Rahmatika Annuranda, Ramansyah Eka Apriyanti -, Apriyanti Ardi Wicaksono ari kusyanti Arieftia Wicaksono Aulia Akhrian Syahidi Aulia Dewi Savitri Aulia Nurrahma Rosanti Paidja Aulia Septi Pertiwi Azhar Izzannada Elbachtiar Azzam Syawqi Aziz Baharudin Yusuf Widiyanto Barlian Henryranu Prasetio Bayu Aji Firmansyah Bayu Sutawijaya Benni A. Nugroho Bere, Stevania Biabdillah, Fajerin Bianca Pingkan Nevista Bintang Fajrianti Brahma Hanif Farhansyah Budi Darma Setiawan Budi Setiawan Cahya, Reiza Adi Cinthia Vairra Hudiyanti Dariswan Janweri Perangin-Angin Dary Ardiansyah Haryono Dea Zakia Nathania Dedi Romario Delpiero, Rangga Raditya Desy Setya Rositasari Dika Imantika Dimas Angga Nazaruddin Dinda Adimanggala Dito William Hamonangan Gultom Diva Fardiana Risa Diva Fardiana Risa Djoko Pramono Dona Adittia Dyah Ayu Wulandari Dyah Ayu Wulandari Dzar Romaita Eka Devi Prasetiya Eka Yuni Darmayanti Eko Laksono Eko Setiawan Elok Nuraida Kusuma Dewi Fabiansyah Cahyo Kuncoro Pradipta Faizatul Amalia Fajar Pradana Fajar Pradana Fajerin Biabdillah Faranisa, Puspa Ayu Fardan Ainul Yaqiin Farhan Setya Dhitama Farid Syauqi Nirwan Fasya Ghassani Hadiyan Fatwa Ramdani, Fatwa Ferdian Maulana Akbar Ferry Ardianto Rismawan Ficry Agam Fathurrachman Fikar Mukamal Gandhi Ramadhona Giga Setiawan Gregorius Dhanasatya Pudyakinarya Gultom, Dito William Hamonangan Gunawan, Alifi Habib Bahari Khoirullah Haikal, Raihan Hanif Prasetyo Maulidina Hanifah Khoirunnisak Hanifah Muslimah Az-Zahra Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haryowinoto Rizqul Aktsar Hasyir Daffa Ibrahim Hayashi, Yusuke Herman Tolle Heryana, Ana Hirashima, Tsukasa Holiyanda Husada Hutamaputra, William Ihza Razan Alghifari Ikhsan Putra Arisandi Ikrom Septian Hadi Ilham Pambudi Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra K. Syahputra Indra Kurniawan Syahputra Indriati Indriati Indriati Indriati Intan Yusuf Habibie Iqbal Taufiq Ahmad Nur Irfani, Ilham Irma Nurvianti Irwan Suprianto Issa Arwani Ivqonnada Al Mufarrih Joseph Ananda Sugihdharma Joseph Ananda Sugihdharma Julia Ferlin Kartiko, Erik Yohan Katrina Puspita Kevin Gusti Farras Fari' Utomo Kharis Alfian Kharis Alfian Kresna Hafizh Muhaimin Krisnabayu, Rifky Yunus Krisnandi, Dikdik Kuncahyo Setyo Nugroho Kurnia Fakhrul Izza Kusumo, R. Budiarianto Suryo Lailil Muflikhah Ludgerus Darell Perwara Luthfi Afrizal Ardhani M Reza Syahputra A M. Ali Fauzi M. Khusnul Azhari M. Raabith Rifqi M. Sofyan Irwanto Mar'i, Farhanna Marvel Timothy Raphael Manullang Mawarni, Marrisaeka Michael Stephen Lui Moch Irfan Prayudha Adhianto Mochamad Chandra Saputra Mochamad Havid Albar Purnomo Mochammad Dearifaldi Al Ikhsan Mochammad Dearifaldi Al Ikhsan Moh Iqbal Yusron Mufidatun Nuha Muh. Edo Aprillia Andilala Muhammad Ferdyandi Muhammad Ifa Amrillah Muhammad Tanzil Furqon Muhammad Taufik Dharmawan Muhammad Wafi Muhammad Wafi Muhammad Zulfikarrahman Nabila Leksana Putri Nabila Lubna Irbakanisa Nadifa, Rahajeng Mufti Nainggolan, Cesilia Natasya Nanang Yudi Setiawan Nanang Yudi Setiawan Nanang Yudi Setyawan Nanda Ajeng Kartini Nanda Samsu Dhuha Nasita Ratih Damayanti Naufal Fathirachman Mahing Nourman Hajar Novanto Yudistira Novi Sunu Sri Giriwati Novianti, Siska Nur Wahyu Melliano Hariyanto Nurafifah Alya Farahisya Nurul Hidayat Oddy Aulia Rahman Nugroho Okta Dwi Ariska Ovy Rochmawanti Pamungkas, Gilang Alif Pradana , Fajar Priyambadha, Bayu Pryono, Muhammad Adam Puras Handharmahua Putra Pandu Adikara Rafif Taqiuddin Rafif Taqiuddin Rafly, Andi Raga Saputra Heri Istanto Rahman, Rafli Rahmat Adi Setiawan Ramadhan, Muhammad Fitrah Randy Cahya Wihandika Randy Cahya Wihandika Ratih Kartika Dewi Refi Fadholi Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renavitasari, Ivenulut Rizki Diaz Retno Indah Rokhmawati Retno Indah Rokhmawati, Retno Indah Revanza, Muhammad Nugraha Delta Reza Syahputra Rezka Aditya Nugraha Hasan Rezky Dermawan Rhobith, Muhammad Rian Nugroho Ridwan Adi Setiabudi Riski Darmawan Riza Setiawan Soetedjo Rizal Setya Perdana Rizkey Wijayanto Rizkia Desi Yudiari Rizky Adinda Azizah Rizky Muhammad Faris Prakoso Robi Dwi Setiawan Rona Salsabila Said Atharillah Alifka Alhabsyi Samuel Arthur Satrio A. Wicaksono Satrio Agung Wicaksono Satrio Agung Wicaksono Satrio Hadi Wijoyo Satrio Hadi Wijoyo Satyawan Agung Nugroho Satyawan Agung Nugroho Shinta Aprilisia Sifaunnufus Ms, Fi Imanur Sintiya, Karena Siswahyudi, Puad Siti Mutdilah Sofyanda, Erika Yussi Sri Wulan Utami Vitandy Sueddi Sihotang Sugihdharma, Joseph Ananda Sulandri Sulandri Sza Sza Amulya Larasati Taufik Hidayat Timothy Julian Titus Christian Ubaydillah, Achmad Afif Utaminingrum, Fitri Vasha Farisi Sarwan Halim Very Sugiarto, Very Vivy Junita Wahyu Ardiansyah, Mohammad Wahyu Satriyo Wibowo Wahyudi, Hafif Bustani Wayan F. Mahmudy Wayan Firdaus Mahmudy Welly Purnomo Whita Parasati Wicky Prabowo Juliastoro Windy Adira Istiqhfarani Wiratama Ahsani Taqwim Wirdhayanti Paulina Yoga Tika Pratama Yudi Muliawan Yuita Arum Sari Zainal Arifien Zayn, Afta Ramadhan